Publications by Freyr Sverrisson

Predicting protein interactions using geometric deep learning on protein surfaces

In the domain of computational structural biology, predicting protein interactions based on molecular structure remains a pivotal challenge. This thesis delves into this challenge through a series of interconnected studies. The first chapter introduces th ...

EPFL2024

De novo design of protein interactions with learned surface fingerprints

Henning Paul-Julius Stahlberg, Didier Trono, Priscilla Turelli, Charlène Mireille Raymonde Raclot, Sandrine Madeleine Suzanne Georgeon, Beat Fierz, Aaron Simone Petruzzella, Anthony Marchand, Bruno Emanuel Ferreira De Sousa Correia, Elisa Oricchio, Zander Harteveld, Pablo Gainza Cirauqui, Freyr Sverrisson, Andreas Scheck, Sarah Wehrle, Stéphane Rosset, Alexandra Krina Van Hall-Beauvais, Alexandra Teslenko, Jane Marsden, Michael Bronstein, Casper Alexander Goverde, Stephen Michael Buckley, Dongchun Ni, Martin Pacesa

Physical interactions between proteins are essential for most biological processes governing life. However, the molecular determinants of such interactions have been challenging to understand, even as genomic, proteomic and structural data increase. This k ...

2023

Systems and methods for de novo design of protein interactions with learned surface fingerprints

Anthony Marchand, Zander Harteveld, Pablo Gainza Cirauqui, Freyr Sverrisson, Andreas Scheck, Sarah Wehrle, Alexandra Krina Van Hall-Beauvais, Michael Bronstein

The present application relates to a computer-implemented systems and methods for protein interaction design using surface fingerprints. The method comprises predicting at least one target interface site with high binding propensity, wherein, optionally, t ...

2023

A method and system for fast end-to-end learning on protein surfaces

Bruno Emanuel Ferreira De Sousa Correia, Pablo Gainza Cirauqui, Freyr Sverrisson

The present invention concerns a computer-system-implemented method for predicting properties of a protein molecule, comprising the steps of: receiving an input representation of the protein molecule; applying a surface generator to produce a molecular sur ...

2022

Fast end-to-end learning on protein surfaces

Bruno Emanuel Ferreira De Sousa Correia, Freyr Sverrisson

Proteins' biological functions are defined by the geometric and chemical structure of their 3D molecular surfaces. Recent works have shown that geometric deep learning can be used on mesh-based representations of proteins to identify potential functional s ...

IEEE COMPUTER SOC2021

De Novo Design of Site-specific Protein Binders Using Surface Fingerprints

Sandrine Madeleine Suzanne Georgeon, Aaron Simone Petruzzella, Elisa Oricchio, Zander Harteveld, Pablo Gainza Cirauqui, Freyr Sverrisson, Andreas Scheck, Sarah Wehrle, Stéphane Rosset, Alexandra Krina Van Hall-Beauvais

WILEY2021

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning

Bruno Emanuel Ferreira De Sousa Correia, Pablo Gainza Cirauqui, Freyr Sverrisson, Michael Bronstein

Predicting interactions between proteins and other biomolecules solely based on structure remains a challenge in biology. A high-level representation of protein structure, the molecular surface, displays patterns of chemical and geometric features that fin ...

2019

Decrypting interaction fingerprints in protein molecular surfaces

Bruno Emanuel Ferreira De Sousa Correia, Pablo Gainza Cirauqui, Freyr Sverrisson, Michael Bronstein

SPRINGER2019

Rosetta FunFolDes - A general framework for the computational design of functional proteins

Bruno Emanuel Ferreira De Sousa Correia, Anne Marie-Thérèse Suzanne Billet, Jaume Bonet Martinez, Fabian Sesterhenn, Che Yang, Sabrina Susan Vollers, Freyr Sverrisson, Mélanie Evelyne Villard, Andreas Scheck, Sarah Wehrle, Roxanne Marine Lourman, Stéphane Rosset, Karen Schriever

The robust computational design of functional proteins has the potential to deeply impact translational research and broaden our understanding of the determinants of protein function and stability. The low success rates of computational design protocols an ...

2018